Swarm Intelligence Method Ant Colony Optimization for Reconfiguration of Distribution System
Sridhar chandrappa masti
, Prof. Kavitha k m
Topology, Ant Colony Optimization, Reconfiguration, Radial.
Network reconfiguration in distribution systems is a process of changing the topology of distribution network by altering the open or closed status of switches. The reconfiguration problem can be formulated as a nonlinear optimization problem with both integer and real variables. The objective of this study is to present a new algorithm to solve the optimal feeder reconfiguration problem, for loss reduction in distribution systems. This employs a heuristic method called Ant Colony Optimization (ACO). The Ant Colony Optimization algorithm is a relatively new and powerful swarm intelligence method for solving optimization problems. It is also called an Ant Colony Search Algorithm (ACSA). It is a population based approach that uses exploration of positive feedback as well as greedy search. The Ant Colony Optimization (ACO) Algorithm was inspired from the natural behavior of ants and tries to emulate them in locating food sources and bring them back to their colony by the formation of unique trials. Therefore, through collection of cooperative agents called “ants”, the near optimal solution to the feeder reconfiguration can be effectively achieved. In addition, the ACSA applies the state transition and Global pheromone updating rules to facilitate the computation. In this project work the presented algorithm involves selecting, among all the possible configurations, the one that incurs the smallest power loss and that satisfies constraints like voltage magnitude, current limit of the branches and Radial topology. The proposed approach is demonstrated using IEEE 16 BUS test system. The simulation code is written in MATLAB software for the analysis.
" Swarm Intelligence Method Ant Colony Optimization for Reconfiguration of Distribution System", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 5, page no.492 - 500, May-2016, Available :https://ijsdr.org/papers/IJSDR1605095.pdf
Volume 1
Issue 5,
May-2016
Pages : 492 - 500
Paper Reg. ID: IJSDR_160376
Published Paper Id: IJSDR1605095
Downloads: 000347057
Research Area: Engineering
Country: davanagere, karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
